O10.6. PRECISION MEDICINE FOR EARLY PSYCHOSIS COORDINATED SPECIALTY CARE: BASELINE FRONTOPARIETAL TASK-RELATED BOLD ACTIVITY PREDICTS CLINICAL IMPROVEMENT AT ONE YEAR FOLLOW-UP IN YOUNG PEOPLE WITH RECENT ONSET PSYCHOSIS. (9th April 2019) - Carter, Cameron; Smucny, Jason; Lesh, Tyler
Abstract: Background: Response to treatment in psychotic disorders is highly variable, and biomarkers of treatment response have been lacking to date. As a result, trial and error remains the basis for care in early psychosis and poor outcomes continue to be common in individuals even when duration of untreated psychosis is relatively short and specialized clinical care is provided. Early identification of patients who are less likely to have good treatment responses would help identify individuals who would benefit from alternative and/or supplemental interventions. Here we evaluated the ability of functional magnetic resonance imaging (fMRI)-based measures of cognitive control related brain activity collected during initial engagement in treatment to predict symptomatic improvement in early psychosis patients after one year. Methods: Patients with either schizophrenia (n = 65, 49M/16F, mean age 20.8 years) or Type I bipolar disorder with psychotic features (n = 17, 9M/8F, mean age 21.6 years) were scanned during the AX CPT task at the beginning of treatment and re-evaluated clinically after 12 months of early psychosis specialty care. 138 healthy controls were included to confirm the AX-CPT was activating frontoparietal networks. Patients were classified as Improvers (> 20% improvement on Brief Psychiatric Rating Scale (BPRS) Total Score at one-year follow-up vs. baseline) or Non-Improvers. Behavioral and functional measures of proactive control during the AX-CPT as well as baseline clinical syndrome scores (Reality Distortion (from BPRS/SAPS), Disorganization (from BPRS/SAPS), Poverty from BPRS/SANS) were evaluated on their ability to predict Improver status. Results: Cognitive control-associated measures significantly predicted Improver status (2. = 9.5, p < 0.01) with 70% positive predictive value, 60% negative predictive value, and 66% accuracy. Only the fMRI-based measure (and not the behavioral measure) significantly predicted status. The addition of syndrome scores did not significantly improve model fit (step 2 = 4.5, p = 0.21), although adding these scores increase accuracy to 70% with 75% positive predictive value and 63% negative predictive value. Discussion: Baseline fMRI data significantly predicted clinical improvement after one year of treatment. Although higher rates of prediction should be pursued, this represents an advance over the limited ability of clinicians to predict treatment response in first-episode patients entering care. fMRI may have potential utility in personalized medicine, as treating patients that present with low frontoparietal activation by specialized interventions (e.g. prefrontal brain stimulation) may improve outcome. Future studies may seek to improve predictive power by combining fMRI with other pathophysiologically relevant neuroimaging measures.